{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# AWS S3 support\n",
    " * Streams in data that is needed \n",
    " * Useful is you spin down/up a AWS machine"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:25:46.414271Z",
     "start_time": "2019-07-13T14:25:45.538770Z"
    }
   },
   "outputs": [],
   "source": [
    "import vaex\n",
    "import numpy as np\n",
    "df = vaex.open('s3://vaex/taxi/yellow_taxi_2015_f32s.hdf5?anon=true')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:25:51.268969Z",
     "start_time": "2019-07-13T14:25:51.197831Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead>\n",
       "<tr><th>#                                      </th><th>vendor_id  </th><th>pickup_datetime              </th><th>dropoff_datetime             </th><th>passenger_count  </th><th>payment_type  </th><th>trip_distance     </th><th>pickup_longitude  </th><th>pickup_latitude   </th><th>rate_code  </th><th>store_and_fwd_flag  </th><th>dropoff_longitude  </th><th>dropoff_latitude  </th><th>fare_amount  </th><th>surcharge  </th><th>mta_tax  </th><th>tip_amount        </th><th>tolls_amount  </th><th>total_amount      </th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "<tr><td><i style='opacity: 0.6'>0</i>          </td><td>VTS        </td><td>2014-12-16 02:26:00.000000000</td><td>2014-12-16 02:28:00.000000000</td><td>1                </td><td>CSH           </td><td>1.090000033378601 </td><td>-73.98672485351562</td><td>40.75642013549805 </td><td>1.0        </td><td>nan                 </td><td>-73.9964599609375  </td><td>40.74289321899414 </td><td>5.0          </td><td>0.5        </td><td>0.5      </td><td>0.0               </td><td>0.0           </td><td>6.0               </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>1</i>          </td><td>VTS        </td><td>2014-12-15 18:23:00.000000000</td><td>2014-12-15 18:58:00.000000000</td><td>2                </td><td>              </td><td>6.28000020980835  </td><td>-74.00418853759766</td><td>40.72119140625    </td><td>1.0        </td><td>nan                 </td><td>-73.97000122070312 </td><td>nan               </td><td>nan          </td><td>nan        </td><td>nan      </td><td>nan               </td><td>nan           </td><td>nan               </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>2</i>          </td><td>VTS        </td><td>2015-01-15 19:05:39.000000000</td><td>2015-01-15 19:23:42.000000000</td><td>1                </td><td>1             </td><td>1.590000033378601 </td><td>-73.993896484375  </td><td>40.7501106262207  </td><td>1.0        </td><td>0.0                 </td><td>-73.97478485107422 </td><td>40.75061798095703 </td><td>12.0         </td><td>1.0        </td><td>0.5      </td><td>3.25              </td><td>0.0           </td><td>17.049999237060547</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>3</i>          </td><td>CMT        </td><td>2015-01-10 20:33:38.000000000</td><td>2015-01-10 20:53:28.000000000</td><td>1                </td><td>1             </td><td>3.299999952316284 </td><td>-74.00164794921875</td><td>40.7242431640625  </td><td>1.0        </td><td>0.0                 </td><td>-73.99441528320312 </td><td>40.75910949707031 </td><td>14.5         </td><td>0.5        </td><td>0.5      </td><td>2.0               </td><td>0.0           </td><td>17.799999237060547</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>4</i>          </td><td>CMT        </td><td>2015-01-10 20:33:38.000000000</td><td>2015-01-10 20:43:41.000000000</td><td>1                </td><td>2             </td><td>1.7999999523162842</td><td>-73.96334075927734</td><td>40.80278778076172 </td><td>1.0        </td><td>0.0                 </td><td>-73.95182037353516 </td><td>40.82441329956055 </td><td>9.5          </td><td>0.5        </td><td>0.5      </td><td>0.0               </td><td>0.0           </td><td>10.800000190734863</td></tr>\n",
       "<tr><td>...                                    </td><td>...        </td><td>...                          </td><td>...                          </td><td>...              </td><td>...           </td><td>...               </td><td>...               </td><td>...               </td><td>...        </td><td>...                 </td><td>...                </td><td>...               </td><td>...          </td><td>...        </td><td>...      </td><td>...               </td><td>...           </td><td>...               </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>146,112,986</i></td><td>VTS        </td><td>2015-12-31 23:59:56.000000000</td><td>2016-01-01 00:08:18.000000000</td><td>5                </td><td>1             </td><td>1.2000000476837158</td><td>-73.99381256103516</td><td>40.72087097167969 </td><td>1.0        </td><td>0.0                 </td><td>-73.98621368408203 </td><td>40.722469329833984</td><td>7.5          </td><td>0.5        </td><td>0.5      </td><td>1.7599999904632568</td><td>0.0           </td><td>10.5600004196167  </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>146,112,987</i></td><td>CMT        </td><td>2015-12-31 23:59:58.000000000</td><td>2016-01-01 00:05:19.000000000</td><td>2                </td><td>2             </td><td>2.0               </td><td>-73.96527099609375</td><td>40.76028060913086 </td><td>1.0        </td><td>0.0                 </td><td>-73.93951416015625 </td><td>40.75238800048828 </td><td>7.5          </td><td>0.5        </td><td>0.5      </td><td>0.0               </td><td>0.0           </td><td>8.800000190734863 </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>146,112,988</i></td><td>CMT        </td><td>2015-12-31 23:59:59.000000000</td><td>2016-01-01 00:12:55.000000000</td><td>2                </td><td>2             </td><td>3.799999952316284 </td><td>-73.98729705810547</td><td>40.739078521728516</td><td>1.0        </td><td>0.0                 </td><td>-73.9886703491211  </td><td>40.69329833984375 </td><td>13.5         </td><td>0.5        </td><td>0.5      </td><td>0.0               </td><td>0.0           </td><td>14.800000190734863</td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>146,112,989</i></td><td>VTS        </td><td>2015-12-31 23:59:59.000000000</td><td>2016-01-01 00:10:26.000000000</td><td>1                </td><td>2             </td><td>1.9600000381469727</td><td>-73.99755859375   </td><td>40.72569274902344 </td><td>1.0        </td><td>0.0                 </td><td>-74.01712036132812 </td><td>40.705322265625   </td><td>8.5          </td><td>0.5        </td><td>0.5      </td><td>0.0               </td><td>0.0           </td><td>9.800000190734863 </td></tr>\n",
       "<tr><td><i style='opacity: 0.6'>146,112,990</i></td><td>VTS        </td><td>2015-12-31 23:59:59.000000000</td><td>2016-01-01 00:21:30.000000000</td><td>1                </td><td>1             </td><td>1.059999942779541 </td><td>-73.9843978881836 </td><td>40.76725769042969 </td><td>1.0        </td><td>0.0                 </td><td>-73.99098205566406 </td><td>40.76057052612305 </td><td>13.5         </td><td>0.5        </td><td>0.5      </td><td>2.9600000381469727</td><td>0.0           </td><td>17.760000228881836</td></tr>\n",
       "</tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "#            vendor_id    pickup_datetime                dropoff_datetime               passenger_count    payment_type    trip_distance       pickup_longitude    pickup_latitude     rate_code    store_and_fwd_flag    dropoff_longitude    dropoff_latitude    fare_amount    surcharge    mta_tax    tip_amount          tolls_amount    total_amount\n",
       "0            VTS          2014-12-16 02:26:00.000000000  2014-12-16 02:28:00.000000000  1                  CSH             1.090000033378601   -73.98672485351562  40.75642013549805   1.0          nan                   -73.9964599609375    40.74289321899414   5.0            0.5          0.5        0.0                 0.0             6.0\n",
       "1            VTS          2014-12-15 18:23:00.000000000  2014-12-15 18:58:00.000000000  2                                  6.28000020980835    -74.00418853759766  40.72119140625      1.0          nan                   -73.97000122070312   nan                 nan            nan          nan        nan                 nan             nan\n",
       "2            VTS          2015-01-15 19:05:39.000000000  2015-01-15 19:23:42.000000000  1                  1               1.590000033378601   -73.993896484375    40.7501106262207    1.0          0.0                   -73.97478485107422   40.75061798095703   12.0           1.0          0.5        3.25                0.0             17.049999237060547\n",
       "3            CMT          2015-01-10 20:33:38.000000000  2015-01-10 20:53:28.000000000  1                  1               3.299999952316284   -74.00164794921875  40.7242431640625    1.0          0.0                   -73.99441528320312   40.75910949707031   14.5           0.5          0.5        2.0                 0.0             17.799999237060547\n",
       "4            CMT          2015-01-10 20:33:38.000000000  2015-01-10 20:43:41.000000000  1                  2               1.7999999523162842  -73.96334075927734  40.80278778076172   1.0          0.0                   -73.95182037353516   40.82441329956055   9.5            0.5          0.5        0.0                 0.0             10.800000190734863\n",
       "...          ...          ...                            ...                            ...                ...             ...                 ...                 ...                 ...          ...                   ...                  ...                 ...            ...          ...        ...                 ...             ...\n",
       "146,112,986  VTS          2015-12-31 23:59:56.000000000  2016-01-01 00:08:18.000000000  5                  1               1.2000000476837158  -73.99381256103516  40.72087097167969   1.0          0.0                   -73.98621368408203   40.722469329833984  7.5            0.5          0.5        1.7599999904632568  0.0             10.5600004196167\n",
       "146,112,987  CMT          2015-12-31 23:59:58.000000000  2016-01-01 00:05:19.000000000  2                  2               2.0                 -73.96527099609375  40.76028060913086   1.0          0.0                   -73.93951416015625   40.75238800048828   7.5            0.5          0.5        0.0                 0.0             8.800000190734863\n",
       "146,112,988  CMT          2015-12-31 23:59:59.000000000  2016-01-01 00:12:55.000000000  2                  2               3.799999952316284   -73.98729705810547  40.739078521728516  1.0          0.0                   -73.9886703491211    40.69329833984375   13.5           0.5          0.5        0.0                 0.0             14.800000190734863\n",
       "146,112,989  VTS          2015-12-31 23:59:59.000000000  2016-01-01 00:10:26.000000000  1                  2               1.9600000381469727  -73.99755859375     40.72569274902344   1.0          0.0                   -74.01712036132812   40.705322265625     8.5            0.5          0.5        0.0                 0.0             9.800000190734863\n",
       "146,112,990  VTS          2015-12-31 23:59:59.000000000  2016-01-01 00:21:30.000000000  1                  1               1.059999942779541   -73.9843978881836   40.76725769042969   1.0          0.0                   -73.99098205566406   40.76057052612305   13.5           0.5          0.5        2.9600000381469727  0.0             17.760000228881836"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:26:05.626081Z",
     "start_time": "2019-07-13T14:26:05.221659Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[########################################]:  100.00% elapsed time  :        0s =  0.0m =  0.0h\n",
      " "
     ]
    },
    {
     "data": {
      "text/plain": [
       "array(245566750)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.passenger_count.sum(progress=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Remote dataframe\n",
    " * Data at server\n",
    " * State changes at client\n",
    " * Server is stateless\n",
    "    * but does some caching for optmization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:26:35.185949Z",
     "start_time": "2019-07-13T14:26:33.871336Z"
    }
   },
   "outputs": [],
   "source": [
    "token = open('token-STSci.txt').read().strip()\n",
    "df = vaex.open(f'ws://ec2-18-222-183-211.us-east-2.compute.amazonaws.com:9000/gaia_ps1_nochunk?token_trusted={token}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:26:37.869718Z",
     "start_time": "2019-07-13T14:26:36.593555Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7fa592b41a90>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot('ra', 'dec', f='log')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-13T14:26:49.433166Z",
     "start_time": "2019-07-13T14:26:49.084163Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Expression = deg2rad(ra)\n",
       "Length: 928,000,000 dtype: float64 (expression)\n",
       "-----------------------------------------------\n",
       "        0  1.99588\n",
       "        1  1.99594\n",
       "        2    1.996\n",
       "        3  1.99602\n",
       "        4  1.99593\n",
       "       ...        \n",
       "927999995  1.95381\n",
       "927999996  1.95404\n",
       "927999997  1.95398\n",
       "927999998   1.9541\n",
       "927999999  1.95396"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR:Thread-4:vaex.remote:unexpected decoding error\n",
      "Traceback (most recent call last):\n",
      "  File \"/home/maartenbreddels/github/vaexio/vaex/packages/vaex-core/vaex/remote.py\", line 185, in _on_websocket_message\n",
      "    json_data, data = msg.split(b\"\\n\", 1)\n",
      "AttributeError: 'NoneType' object has no attribute 'split'\n"
     ]
    }
   ],
   "source": [
    "np.deg2rad(df.ra)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# xarray support\n",
    " * binby instead of groupby"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-12T20:14:54.784887Z",
     "start_time": "2019-07-12T20:14:48.464825Z"
    }
   },
   "outputs": [],
   "source": [
    "import vaex\n",
    "df = vaex.open('/data/yellow_taxi_2009_2015_f32.hdf5')\n",
    "df = df.dropna(column_names=['dropoff_latitude', 'dropoff_longitude', 'pickup_latitude'])\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-11T22:34:51.365960Z",
     "start_time": "2019-07-11T22:34:34.556457Z"
    }
   },
   "outputs": [],
   "source": [
    "# Define a mapping dictionary\n",
    "map_payment_type = {'csh': 2, 'crd': 1, 'cash': 2, '1': 1, 'cas': 2, '2': 2, 'credit': 1, 'cre': 1, 'unk': 5, \n",
    "                    'noc': 3, 'no charge': 3, '3':3, 'dis': 4, 'no ': 3, '4': 4, 'dispute': 4, 'na ': 5, '5':5}\n",
    "\n",
    "df['payment_type'] = df.payment_type.str.lower().map(map_payment_type, \n",
    "                                                                  default_value=7, \n",
    "                                                                  allow_missing=True) -1\n",
    "df.categorize(df.payment_type, labels=['Credit card', 'Cash', 'No charge', 'Dispute', 'Unknown', 'Voided trip', 'NA'],\n",
    "             check=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-11T22:35:46.180738Z",
     "start_time": "2019-07-11T22:34:51.367955Z"
    }
   },
   "outputs": [],
   "source": [
    "da = df.binby([\n",
    "    vaex.groupby.BinnerTime.per_month(df.pickup_datetime),\n",
    "    df.payment_type\n",
    "], agg='count')\n",
    "da"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-11T22:35:54.767941Z",
     "start_time": "2019-07-11T22:35:54.246847Z"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pylab as plt\n",
    "plt.figure(figsize=(10,6), dpi=200)\n",
    "np.log10(da).plot(hue='payment_type');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
